MLB Baseball

SF vs LAD Prediction

May 14, 2026

10,000 Monte Carlo simulations

SF vs LAD prediction for May 14, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects LAD 3.3 - SF 3.4. LAD is favored with a 50.8% win probability. The run line is -1.5 and the total is 8.0. Model projects 6.6 total runs.

LAD
3.3
Projected Score
VS O/U 8.0
SF
3.4
Projected Score
Win Probability
50.8%
49.2%
LADSF
-1.5
Run Line (LAD)
8.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 53.5% (2,063 games)

Projected Runs Range 10th – 90th percentile

SF
135
LAD
135
FINALLAD 5 — SF 2
Projected
LAD 3.3 — SF 3.4
Actual
LAD 5 — SF 2

Starting Pitcher Matchup

Landen Roupp R
SF
SI37%93 mph10% whiff
CU29%76 mph31% whiff
CH19%87 mph29% whiff
Emmet Sheehan R
LAD
FF41%94 mph26% whiff
SL32%87 mph40% whiff
CH17%85 mph23% whiff

Weather Impact

Dodger Stadium
64°F7 mph wind
HR: 0.986 Total: 0.990
7mph in

Bullpen Comparison

SF
3.35ERA
4.10FIP
7.73K/9
4.86BB/9
1.35WHIP
LAD
3.55ERA
3.16FIP
9.63K/9
3.59BB/9
1.23WHIP

Betting Edges

RUN_LINE AWAY +1.5
-35.0% EV
-147
TOTAL OVER 8.0
-34.3% EV
+100
RUN_LINE HOME -1.5
-23.6% EV
+122
F5_ML HOME
-18.2% EV
-167
ML HOME
-15.6% EV
-172
ML AWAY
+13.7% EV
+144

First 5 Innings & NRFI

SF F5
1.9 runs
41.3% win
LAD F5
1.8 runs
38.6% win
F5 Total
3.6
NRFI
64.3%
YRFI
35.7%
Avg 1st Inn Runs
0.70

HR Spotlight

Avg HRs
1.8
Over 0.5 HR
83%
Over 1.5 HR
53%
No HR
17%

Pitcher Strikeout Projections

Landen Roupp
0.0 K projected
SF | K/9: 0.0
Emmet Sheehan
0.0 K projected
LAD | K/9: 0.0

Injury Report

SF8 injured
Daniel Susac C10-DAY-IL
Jason Foley RP60-DAY-IL
Erik Miller RP15-DAY-IL
Logan Webb SP15-DAY-IL
Jared Oliva CF60-DAY-IL
Rowan Wick RP60-DAY-IL
+2 more
LAD8 injured
Ben Casparius RP15-DAY-IL
Edwin Diaz RP60-DAY-IL
Brock Stewart RP15-DAY-IL
Tommy Edman 2B60-DAY-IL
Tyler Glasnow SP15-DAY-IL
Landon Knack SP60-DAY-IL
+2 more

AI Intelligence Analysis

LEAN +1RED ZONE45.6% WR (n=146)
SF away +144 (41% implied) vs model 46.6% (13.7% edge) — massive 9.8pp market undervalue. Pitcher advantage SF (Roupp 3.34 vs Sheehan 5.17 ERA). Dodger Stadium park suppressive (0.92), wind in (-6.9). Market is severely overpricing LAD home team (-172). However, edge 13.7% EXCEEDS calibration caps and lands in RED zone (away ML). LEAN not BET; reduce units.

Key Factors

  • Pitcher mismatch significant: Roupp 3.34 ERA (28.7% K, B-) vs Sheehan 5.17 ERA (28.1% K, B). Same K-rate but Roupp has 1.83 ERA advantage — away team better pitcher.
  • Market-model gap massive: LAD 63.2% market vs model 53.4% = 9.8pp delta. Second-largest gap on entire slate (only behind DET @ NYM which was WRONG). Market is heavily on LAD name/home field.
  • Park factor 0.92 (8% suppression) + wind in (-6.9 mph) = pitcher-dominant environment. Run suppression ~0.5-0.75 runs estimated. Roupp benefits, Sheehan penalized.
  • UNDER 8.0 edge 12.5% complementary — model 6.63 vs market 8.0 validates pitcher + park narrative.
  • F5 SF ML edge 13.3% strong — early innings heavily favor SF pitcher advantage.

Risk Factors

  • Edge 13.7% is ABOVE calibration caps (12% ML max); historical data shows 15%+ edges have 38% WR. Red zone away ML worst performer.
  • Market's massive lean on LAD (-172) suggests sharps may know something model doesn't (recent form? lineup health? bullpen?). Sharp money often correct on heavy home favorites.
  • Away ML in RED zone (45.6% WR) is WORST zone on slate — even with legitimate edge, zone history warns against. Confidence capped at +1 not +2.
Sharp MoneyAgainst ModelMarket LAD -172 (heavy home) suggests sharp money on Dodgers despite model's pitcher advantage lean. Sharp positioning against model, but model's edge (pitcher + park) has concrete backing.
HIGH EDGE WARNINGRED ZONEMASSIVE MARKET MISPRICEPITCHER ADVANTAGEPARK SUPPRESSIONF5 EDGE

Edge Analysis

Moneyline
LAD 50.8%
-23.6 pts
Run Line
-1.5
-23.6 pts
Total
8.0
+12.5 pts
How this prediction was generated: This page shows output from the Olympus Bets MLB Baseball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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